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RAVR: Reference-Answer-guided Variational Reasoning for Large Language Models

arXiv — cs.CL•Thursday, October 30, 2025 at 4:00:00 AM
PositiveArtificial Intelligence
A new study introduces RAVR, a method that enhances the reasoning capabilities of large language models through reinforcement learning. This approach addresses the challenge of generating effective reasoning paths, especially for complex tasks where the models may struggle. By leveraging insights from cognitive science, RAVR aims to improve the decision-making processes of these models, making them more efficient and reliable. This advancement is significant as it could lead to more intelligent AI systems that better understand and respond to human queries.
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